Skip to main content

Python interface to JAGS library for Bayesian data analysis.

Project description

PyJAGS: The Python Interface to JAGS

PyJAGS provides a Python interface to JAGS, a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation.

PyJAGS adds the following features on top of JAGS:

  • Multicore support for parallel simulation of multiple Markov chains (See Jupyter Notebook Advanced Functionality
  • Saving sample MCMC chains to and restoring from HDF5 files
  • Functionality to merge samples along iterations or across chains so that sampling can be resumed in consecutive chunks until convergence criteria are satisfied
  • Connectivity to the Bayesian analysis and visualization package Arviz

License: GPLv2

Installation

A working JAGS installation is required.

    pip install pyjags

Useful Links

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyjags-1.3.3.tar.gz (175.2 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page